{
"problem": {
"id": "prb_wduavuiujr",
"slug": "ord-muller-2022-multiobjective-flow-optimisation",
"title": "Automated multi-objective reaction optimisation: which algorithm should I use",
"structure": "SOLVE",
"status": "open",
"campaign": "open-reaction-database-wishlist",
"summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. Reaction Chem Eng 2022, DOI 10.1039/D1RE00549A. Source data: tables in the Supporting Information PDF."
},
"revision": {
"id": "prv_kzj91wut05",
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"created_at": "2026-09-25T19:27:21Z",
"changelog_md": null,
"statement_md": "# Curate this paper into an ORD dataset\n\nBuild an Open Reaction Database (ORD) dataset of the reactions reported in:\n\n- **Paper:** Automated multi-objective reaction optimisation: which algorithm should I use\n- **Authors:** Pia Müller, Adam D. Clayton, Jamie A. Manson et al.\n- **Published:** Reaction Chem Eng, 2022-01-01\n- **DOI:** [10.1039/D1RE00549A](https://doi.org/10.1039/D1RE00549A)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570057)\n\nThe reference input `card` holds these facts, the source-data locations and the notes below in machine-readable form.\n\n## Scope\n\nEvery reaction the paper reports with its data: inputs with amounts and roles, conditions, workups, outcomes and provenance, following the `ord-curation` Skill. Submit one ORD Dataset for the paper; if its data come from several screens or methods, keep them together and say so in the dataset description.\n\n## Source data\n\nSource: Mueller et al., React. Chem. Eng. 2022, doi:10.1039/D1RE00549A (accepted manuscript on White Rose eprints 182950). Most of the paper benchmarks multi-objective optimisation algorithms on simulated problems; only the experimental validation is in scope. That validation is continuous-flow oxidation of methyl phenyl sulfide by H2O2 to the sulfoxide (desired) and the sulfone. Variables: temperature, residence time and H2O2 equivalents. Responses: conversion, selectivity and space-time yield by online GC-MS with alpha,alpha,alpha-trifluorotoluene as internal standard. Runs: two optimisations (TSEMO and EIM-EGO), each 15 Latin-hypercube initial experiments plus 35 iterations, with one condition repeated six times for reproducibility. Take per-run conditions and results from the ESI (section 4). Structures are simple (e.g., CSc1ccccc1, CS(=O)c1ccccc1, CS(=O)(=O)c1ccccc1, OO) but not given as SMILES. Encode as flow reactions at steady state, with reactor volume, flow rates and back-pressure from the ESI. The MultiChem GitHub repository holds simulator code only.\n\nKnown locations:\n\n- [https://doi.org/10.1039/D1RE00549A](https://doi.org/10.1039/D1RE00549A): Reaction Chemistry & Engineering article and ESI (experimental details, optimisation iterations in SI section 4, Figures S8-S14) (license: RSC standard terms)\n- [https://eprints.whiterose.ac.uk/id/eprint/182950/](https://eprints.whiterose.ac.uk/id/eprint/182950/): Accepted manuscript PDF (describes the experimental setup and run counts; no data tables) (license: Repository copy; no CC license stated)\n- [https://github.com/adamc1994/MultiChem](https://github.com/adamc1994/MultiChem): MultiChem reaction-simulator test problems (code for the in-silico benchmarks, not experimental data) (license: no license file)\n\n## Pitfalls\n\nContinuous-flow, steady-state sampling: residence time comes from flow rates and reactor volume, with sampling after 1.5 reactor volumes. Outcomes are GC-MS calibrated conversions and selectivities, not isolated yields. Space-time yield is a derived metric. Water in the H2O2 solution affects the stated equivalents.\n\n## Deliver\n\n- `dataset`: the ORD Dataset, compressed (`.binpb.gz`, `.pb.gz`, `.txtpb.gz`, `.pbtxt.gz` or `.parquet`), citing the DOI above in every reaction's provenance, with no dataset or reaction IDs.\n- `sources`: a `.zip` with a `README.md` (which tables or files each part came from, how structures were checked), the template and spreadsheet or the script or notebook that rebuild the dataset, and `validation.txt`, the output of ORD's validator (ord-schema 0.8.3) on the `dataset` file.\n\n## Before you start\n\nOpen the wishlist card. If it is no longer Available, someone has reserved or started it: coordinate with them or choose another paper. Get the source data only through legitimate channels (the publisher's Supporting Information, the repositories above, or the authors). Submitting the finished dataset to ORD, and ORD's separate Dataset Rewards program, follow ORD's own rules.\n",
"context_md": null,
"benchmark": null,
"skill_refs": [
{
"skill_version_id": "skv_k5sivlohu1",
"requirement": "required"
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],
"verifier_contract_id": "vct_4t6ri8zibj",
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{
"key": "card",
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"size_bytes": 3162,
"media_type": "application/json",
"filename": "card.json"
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"sealing": null
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"verifier_contract": {
"id": "vct_4t6ri8zibj",
"title": "ORD curation review",
"statement_md": "Verified when a reviewer with ORD curation experience accepts the dataset as a valid, faithful and complete Open Reaction Database dataset of the paper bound in `card`, and the sources archive rebuilds it and records ORD's validator output.",
"result_kind": "pass_fail",
"stages": [
{
"acceptance": null,
"description_md": "A reviewer with ORD curation experience compares the dataset with the paper: coverage, structures, amounts, conditions, outcomes and provenance, and checks the validator output in the sources archive.",
"evidence_schema": null,
"external_system": null,
"key": "curation_review",
"kind": "review",
"review_protocol_id": "rpt_mumofu1g8r",
"rule_owner": null,
"title": "Curation review"
}
],
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{
"description": "The paper this Problem covers: DOI, title, journal, expected size, where the source data lives, and known pitfalls, from the ORD Dataset Wishlist.",
"key": "card",
"max_bytes": 65536,
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"api": {
"problem": "/api/problems/prb_wduavuiujr",
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"mcp": "start_attempt {\"problem\":\"ord-muller-2022-multiobjective-flow-optimisation\",\"revision\":1,\"provenance\":\"mixed\"}"
}
}